1. Field of the Invention
This invention relates generally to the field of signal analyzers and, more particularly, to a signal analyzer designed to measure the amplitude probability distribution of electrical signals. In greater particularity, the invention relates to a signal analyzer designed to measure the amplitude probability density function of noise signals to allow characterization of the signal's statistics in terms of skewness, clipping, kurtosis and other non-Gaussian deviations.
2. Description of the Related Art
In the past, the Gaussianicity of noise signals was estimated by measuring the signal's cumulative amplitude distribution. This measurement was done through repetitive sampling of signal amplitude in combination with computer analysis, or by a simple comparator circuit such as that described on pages 272-274 of the Dec. 11, 1986 EDN magazine article titled, "Test whether a noise source is Gaussian."
The cumulative amplitude distribution function gives the probability that a variable will assume a value equal to or greater than a particular value over a range of values. By the cumulative amplitude distribution method, the relative Gaussianicity of noise signals is determined by the degree of conformance of measured data to a theoretical cumulative distribution curve.
A limitation of the cumulative amplitude distribution method is that measured data do not show the actual distribution of amplitudes. Because of this, departures of data from the theoretical curve do not characterize precisely how a noise signal is different from true Gaussian noise. As will be visually depicted in this disclosure, this method indicates non-Gaussianicity only by a departure of the signal's plotted distribution from the theoretical cumulative amplitude distribution curve. Abnormal characteristics of the noise signal such as skewness, kurtosis, clipping and other non-Gaussian deviations cannot be readily identified.
The cumulative amplitude distribution method can also be relatively insensitive and give results that are difficult to relate to in Gaussian terms, thereby making it difficult to judge the overall degree of non-Gaussianicity of noise signals.
Another probability distribution is the amplitude probability density distribution. This distribution gives the probability that a variable will assume a value near any particular value in its range of values.
Techniques exist for calculating amplitude probability density distributions. One such technique is described in U.S. Pat. No. 3,626,168 issued to Keith H. Norsworthy. This patent describes an invention capable of a multitude of signal measurements. For measurements of amplitude probability density distribution, this invention outputs an indicating signal when an input signal falls between two known signal levels. The indicating signal is then apparently sent to an averaging bin to provide a digitally constructed density distribution. The '168 patent describes an invention that is highly complex and because of the use of a finite number of averaging bins, it cannot provide continuous resolution capability.
In a second scheme, the amplitude probability density distribution is determined through an invention described in U.S. Pat. No. 3,581,200. This invention produces a probability density function profile through the use of a wave generator, spectrum analyzer, sweep generator and x-y recorder. The '200 invention converts signal amplitude distributions into a frequency domain profile for visualization by way of the spectrum analyzer. The invention is of relative high complexity, and nature of the design appears to make system calibration difficult.
In a related but different area, the invention of U.S. Pat. No. 4,625,283 issued to James R. Hurley describes an invention designed to analyze repetitive signals, e.g. sinewave signals. This invention measures the elapsed times it takes for an alternating current signal to cross predetermined reference values and compares these with known values to determine characteristics of an alternating current signal being analyzed. Signal characteristics such as frequency, size of direct current offset and waveform amplitude apparently can be determined with this invention.
A need thus exists for a simple, calibrated device that permits continuous resolution of signal amplitude probability distribution. Such an invention should be able to readily permit the perception of noise signal skewness, kurtosis, clipping, as well as other non-Gaussian deviations.